System and Method for Verifying Positional and Spatial Information Using Depth Sensors

3. The method of claim 2, wherein each set of parameters associated with each sensor of the one or more sensors includes: (a) intrinsic parameters including internal sensor data fixed to a sensor configuration to allow for an accurate mapping between sensor coordinates and pixel coordinates in the image frame; and (b) extrinsic parameters including a location and orientation of each sensor of the one or more sensors relative to the machine in the workspace.

4. The method of claim 2, further comprising generating, via the analysis module, a corresponding synthetic binary mask to retrieve only the machine depth pixels associated with the machine from each depth map.

5. The method of claim 2, wherein the machine data includes: (a) a machine model that includes information relating to degrees of freedom and actuation of the machine; and (b) machine movement information containing a current spatial pose for one or more links of the machine.

6. The method of claim 2, further comprising communicating, via the analysis module, with a corresponding sensor of the one or more sensors to evaluate sensor performance based on the match rate for the comparison of the depth map and the synthetic depth map related to the corresponding sensor.

8. The method of claim 7, further comprising applying, via the analysis module, a machine clustering process to the first three-dimensional occupancy map to isolate a cluster of pixels in the first three-dimensional occupancy map containing only machine occupancy data.

11. The system of claim 9, wherein each set of parameters associated with each sensor of the one or more sensors includes: (a) intrinsic parameters including internal sensor data fixed to a sensor configuration to allow for an accurate mapping between sensor coordinates and pixel coordinates in the image frame; and (b) extrinsic parameters including a location and orientation of each sensor of the one or more sensors relative to the machine in the workspace.

12. The system of claim 9, wherein the analysis module is further operable to generate a corresponding synthetic binary mask to retrieve only the machine depth pixels associated with the machine from each depth map.

13. The system of claim 9, wherein the machine data includes: (a) a machine model that includes information relating to degrees of freedom and actuation of the machine; and (b) machine movement information containing a current spatial pose for one or more links of the machine.

14. The system of claim 9, wherein the analysis module is further operable to communicate with a corresponding sensor of the one or more sensors to evaluate sensor performance based on the match rate for the comparison of the depth map and the synthetic depth map related to the corresponding sensor.

16. The system of claim 15, wherein the analysis module is further operable to apply a machine clustering process to the first three-dimensional occupancy map to isolate a cluster of pixels in the first three-dimensional occupancy map containing only machine occupancy data.

18. The system of claim 17, wherein the analysis module is further operable to compare the machine depth pixels for each depth map with corresponding machine depth pixels for each synthetic depth map to determine a match rate for each comparison, and wherein the signal to the machine is further based on the match rate for each comparison.

19. The system of claim 18, wherein the analysis module is further operable to communicate with a corresponding sensor of the one or more sensors to evaluate sensor functionality based on the match rate for the comparison of the depth map and the synthetic depth map related to the corresponding sensor.